基于改进变邻域搜索算法的多批次协同任务规划

目的 对多批次协同任务进行分析与建模，并研究任务规划的求解算法。方法 以车载装备多批次协同执行任务为例，综合考虑时间协同、任务区域协同和补给区域协同约束，以暴露时间最短为目标函数建立模型，并提出一种改进变邻域搜索算法进行求解，该方法根据邻域的优化能力自动调整迭代时选择该邻域的概率。结果 仿真结果表明，改进策略在不降低最优解质量的情况下，能够避免标准变邻域搜索算法后期易出现某些邻域长时间无法寻找到最优解的情况，有效提高了算法的效率。结论 变邻域搜索算法可以解决多批次任务规划问题，改进后的算法减少了后期对优化能力不强的邻域的搜索次数，有效提升了算法效率。

Multi-batch Collaborative Task Planning Based on Improved Variable Neighborhood Search Algorithm

The work aims to analyze and model multi-batch collaborative tasks, and to study the algorithm of task planning. In this work, vehicle-mounted equipment multi-batch collaborative task was analyzed and modeled. In the modeling process, the constraints of time collaboration, task area collaboration and replenishment area collaboration were integrated, and the minimum exposure time was taken as the objective function. The simulation results showed that the improved strategy could avoid the situation that some neighborhoods could not find the optimal solution for a long time in the later stage of the standard variable neighborhood search algorithm, and improve the efficiency of the algorithm without reducing the quality of the optimal solution. It is concluded that the variable neighborhood search algorithm can solve the multi-batch task planning problem. The improved algorithm reduces the search times of the neighborhood with weak optimization ability in the later stage, and effectively improves the efficiency of the algorithm.